This paper is in the following e-collection/theme issue:

RCTs - Protocols/Proposals (funded, already peer-reviewed, eHealth) (355) Speech and Phonetics in Verbal Protocols (Think Aloud, Recall, and Explanation Tasks) (93)

Published on in Vol 12 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/46970, first published .
Detecting Clinically Relevant Emotional Distress and Functional Impairment in Children and Adolescents: Protocol for an Automated Speech Analysis Algorithm Development Study

Detecting Clinically Relevant Emotional Distress and Functional Impairment in Children and Adolescents: Protocol for an Automated Speech Analysis Algorithm Development Study

Detecting Clinically Relevant Emotional Distress and Functional Impairment in Children and Adolescents: Protocol for an Automated Speech Analysis Algorithm Development Study

Authors of this article:

Yared Alemu1, 2 Author Orcid Image ;   Hua Chen3 Author Orcid Image ;   Chenghao Duan3 Author Orcid Image ;   Desmond Caulley3 Author Orcid Image ;   Rosa I Arriaga3 Author Orcid Image ;   Emre Sezgin4 Author Orcid Image
Article Authors Cited by (4) Tweetations (9) Metrics

Journals

  1. Caulley D, Alemu Y, Burson S, Cárdenas Bautista E, Abebe Tadesse G, Kottmyer C, Aeschbach L, Cheungvivatpant B, Sezgin E. Objectively Quantifying Pediatric Psychiatric Severity Using Artificial Intelligence, Voice Recognition Technology, and Universal Emotions: Pilot Study for Artificial Intelligence-Enabled Innovation to Address Youth Mental Health Crisis. JMIR Research Protocols 2023;12:e51912 View
  2. Toki E, Zakopoulou V, Tatsis G, Pange J. Automated Detection of Neurodevelopmental Disorders Using Face-to-Face Mobile Technology Among Typically Developing Greek Children: Randomized Controlled Trial. JMIR Formative Research 2024;8:e53465 View
  3. Aguirre Vergara F, Pinker I, Fischer A, Seuring T, Tichomirowa M, de Beaufort C, Kamp S, Fagherazzi G, Aguayo G. Readiness of adults with type 1 diabetes and diabetes caregivers for diabetes distress monitoring using a voice-based digital health solution: insights from the PsyVoice mixed methods study. BMJ Open 2025;15(1):e088424 View